Agent Guidance and QA Monitoring

Provides real-time in-workspace agent guidance during live calls and automates quality and compliance monitoring across contact center interactions to reduce handling time, improve consistency, and lower regulatory risk.

The Problem

“Call Center Agent Guidance and QA Monitoring for Faster, Safer Customer Service”

Organizations face these key challenges:

1

Agents switch across multiple systems during live calls and miss relevant context

2

Live-call handling is inconsistent across agents, shifts, and locations

3

After-call wrap-up is slow and often incomplete or inaccurate

4

Manual QA sampling reviews too few calls to catch systemic issues

Impact When Solved

Reduce average handle time through in-workspace guidance and auto-summarizationLower after-call work by generating structured notes, dispositions, and follow-up actionsIncrease consistency of live-call handling across agents and teamsExpand QA coverage from manual sampling to all recorded interactions

The Shift

Before AI~85% Manual

Human Does

  • •Search CRM, knowledge, scripts, and policy sources during live calls
  • •Guide customers manually and decide next steps from static scripts
  • •Write call notes, summaries, dispositions, and follow-up actions after calls
  • •Review a small sample of recorded calls for QA and compliance

Automation

    With AI~75% Automated

    Human Does

    • •Use AI guidance during calls and choose the appropriate customer response
    • •Review and approve AI-drafted summaries, dispositions, and follow-up actions when needed
    • •Validate flagged compliance or quality exceptions and decide escalations

    AI Handles

    • •Transcribe live and recorded conversations and assemble relevant customer and policy context
    • •Surface next-best guidance and approved knowledge snippets during live calls
    • •Generate structured call summaries, notes, dispositions, and action items
    • •Evaluate interactions against quality and compliance criteria at scale

    Operating Intelligence

    How it works

    AI runs the first three steps autonomously.

    Humans own every decision.

    The system gets smarter each cycle.

    Confidence79%
    ArchetypeRecommend & Decide
    Shape6-step converge
    Human gates1
    Autonomy
    67%AI controls 4 of 6 steps

    Who is in control at each step

    Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.

    Loop shapeconverge

    Step 1

    Assemble Context

    Step 2

    Analyze

    Step 3

    Recommend

    Step 4

    Human Decision

    Step 5

    Execute

    Step 6

    Feedback

    AI lead

    Autonomous execution

    1AI
    2AI
    3AI
    5AI
    gate

    Human lead

    Approval, override, feedback

    4Human
    6↺ Loop
    AI-led step
    Human-controlled step
    Feedback loop
    TL;DR

    AI handles assembly, analysis, and execution. The human gate sits at the decision point. Every cycle refines future recommendations.

    The Loop

    6 steps

    1 operating angles mapped

    Operational Depth

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